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| from typing import Callable, List, Optional, Union
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|
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| import mmengine
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| from mmengine.fileio import exists
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|
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| from mmaction.registry import DATASETS
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| from mmaction.utils import ConfigType
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| from .base import BaseActionDataset
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|
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| @DATASETS.register_module()
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| class ActivityNetDataset(BaseActionDataset):
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| """ActivityNet dataset for temporal action localization. The dataset loads
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| raw features and apply specified transforms to return a dict containing the
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| frame tensors and other information. The ann_file is a json file with
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| multiple objects, and each object has a key of the name of a video, and
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| value of total frames of the video, total seconds of the video, annotations
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| of a video, feature frames (frames covered by features) of the video, fps
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| and rfps. Example of a annotation file:
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|
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| .. code-block:: JSON
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| {
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| "v_--1DO2V4K74": {
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| "duration_second": 211.53,
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| "duration_frame": 6337,
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| "annotations": [
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| {
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| "segment": [
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| 30.025882995319815,
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| 205.2318595943838
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| ],
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| "label": "Rock climbing"
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| }
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| ],
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| "feature_frame": 6336,
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| "fps": 30.0,
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| "rfps": 29.9579255898
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| },
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| "v_--6bJUbfpnQ": {
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| "duration_second": 26.75,
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| "duration_frame": 647,
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| "annotations": [
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| {
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| "segment": [
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| 2.578755070202808,
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| 24.914101404056165
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| ],
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| "label": "Drinking beer"
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| }
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| ],
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| "feature_frame": 624,
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| "fps": 24.0,
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| "rfps": 24.1869158879
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| },
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| ...
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| }
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| Args:
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| ann_file (str): Path to the annotation file.
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| pipeline (list[dict | callable]): A sequence of data transforms.
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| data_prefix (dict or ConfigDict): Path to a directory where videos are
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| held. Defaults to ``dict(video='')``.
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| test_mode (bool): Store True when building test or validation dataset.
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| Default: False.
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| """
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|
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| def __init__(self,
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| ann_file: str,
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| pipeline: List[Union[dict, Callable]],
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| data_prefix: Optional[ConfigType] = dict(video=''),
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| test_mode: bool = False,
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| **kwargs):
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| super().__init__(
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| ann_file,
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| pipeline=pipeline,
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| data_prefix=data_prefix,
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| test_mode=test_mode,
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| **kwargs)
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|
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| def load_data_list(self) -> List[dict]:
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| """Load annotation file to get video information."""
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| exists(self.ann_file)
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| data_list = []
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| anno_database = mmengine.load(self.ann_file)
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| for video_name in anno_database:
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| video_info = anno_database[video_name]
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| feature_path = video_name + '.csv'
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| feature_path = '%s/%s' % (self.data_prefix['video'], feature_path)
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| video_info['feature_path'] = feature_path
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| video_info['video_name'] = video_name
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| data_list.append(video_info)
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| return data_list
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|
